In the oil and gas industry, experts evaluate the potential of an area to contain hydrocarbon source rocks in order to identify, assess, and exploit potential hydrocarbon resources. Source-rock presence is a critical aspect of all hydrocarbon systems, and a robust and systematic means to evaluate source-rock presence and quality is a key business need. Neither source-rock presence nor quality nor the processes that control source-rock presence and quality can be detected or measured directly from the remote sensing data (e.g., seismic data, well logs) typically available in exploration settings.
Hydrocarbon source rocks are defined as fine-grained rocks that in their natural state can generate commercial quantities of hydrocarbons. This definition convolves the original organic-matter content of a rock upon deposition with its subsequent burial and heating of the organic matter to yield hydrocarbons that can migrate into an oil or gas field. In this document, the more generic term organic-matter-rich rock (“ORR”) is used to denote the original state of the rock upon deposition and early burial (up to about 3 m deep) and its original content of organic matter. Source-rock quality refers to the amount and type of hydrocarbon that an ORR can generate assuming subsequent burial and heating; it is typically characterized by total organic carbon content (“TOC”, defined as the weight percentage of organic carbon per gram of rock sample), hydrogen content (typically measured as hydrogen index, “HI,” defined as “an indication of the remaining hydrocarbon-generative capacity of a kerogen, as measured by Rock-Eval pyrolysis; hydrogen index is expressed as mg of hydrocarbon per g of TOC” (Waples, Geochemistry in Petroleum Exploration, IHRDC, Boston (1985)), and lithology, and classified according to source-rock rating categories and potential for generating hydrocarbons (oil, condensate, and/or gas). Thus the term ORR refers to prehistoric time and the term source rock refers to the present day character.
Geoscientists are commonly interested in source-rock quality, which is commonly related to the likelihood of generating commercial quantities of hydrocarbons from a source rock. Early examples of simplistic or empirical source-rock predictions relied almost exclusively upon estimates of primary organic-matter production driven by nutrients supplied by ocean upwelling through direct comparisons with organic-matter production rates in modern oceans (As discussed below in the description of the present invention, this is not appropriate for estimates of organic-matter production throughout geological time intervals because of significant changes through evolution in the types of organisms that produce organic matter.) Examples claiming this approach include: Parrish, “Upwelling and petroleum source beds, with reference to Paleozoic,” American Association of Petroleum Geologists Bulletin 66, 750-774 (1982); Barron, “Numerical climate modeling, a frontier in petroleum source rock prediction: results based on Cretaceous simulations,” American Association of Petroleum Geologists Bulletin 69, 448-459 (1985); and Kruis and Barron, “Climate model prediction of paleoproductivity and potential source-rock distribution,” American Association of Petroleum Studies in Geology 30, 195-216 (1990). Another system that claimed to provide source-rock predictions concentrated on preservation of organic matter in deep-marine environments and relied almost exclusively on estimating dissolved oxygen content at the sediment-water interface using semi-quantitative and deterministic algorithms: Westrich et al., 1993, “SORCER; a comprehensive paleogeographic, stratigraphic, and geochemical model for marine source rock prediction,” American Association of Petroleum Geologists 1993 annual convention, Annual Meeting Abstracts, American Association of Petroleum Geologists and Society of Economic Paleontologists and Mineralogists, p. 199 (1993). Yet another approach, the “Source Rock Prediction System” was an early computer system that claimed to provide source-rock prediction—“a simple, microcomputer-implemented, knowledge—based system designed around a decision tree structure,” it relied exclusively on deterministic combinations of a subset of controlling factors to provide a single deterministic estimate of source-rock quality at a single point: Fowler, “Knowledge-Based System for Source Rock Prediction” (meeting abstract), American Association of Petroleum Geologists Bulletin, 71, 557 (1987).
Currently existing predictive schemes for source-rock quality emphasize primary organic-matter production or organic-matter preservation to the practical exclusion of other processes, and use only empirical relations, or rely on a single linear/serial pathway from primary production of organic-matter to accumulation of potential source rocks to estimate source-rock quality. Following are summaries of three models in the recent published literature: OF-Mod, Merlin, and SourceRocker.
OF-Mod
“OF-Mod” is software for organic facies/source rock forward modeling developed by SINTEF, www.sintef.no/content/page1—1074.aspx. The abbreviation SINTEF means The Foundation for Scientific and Industrial Research at the Norwegian Institute of Technology (“NTH”). The SINTEF Group is the largest independent research organization in Scandinavia. SINTEF cooperates closely with the Norwegian University of Science and Technology (“NTNU”) and the University of Oslo.
OF-Mod claims to simulate processes that affect the deposition and preservation of organic matter in a sedimentary basin and the interactions among these processes. It claims to consider marine and terrigenous organic matter supply, upwelling, oxygen minimum zones, degradation in the water column, and burial efficiency. Models in OF-Mod are based on only two input parameters: 1) present-day geometry (thickness and area) of postulated source rock interval or intervals (i.e., multiple geological ages) and 2) reconstructions of palaeo-bathymetry for the top and base of each postulated source-rock interval. Marine organic-matter production is modeled primarily as a function of the distance from shore. Additional areas of higher marine organic-matter production (e.g. upwelling zones) must be explicitly defined by the user as a function of distance offshore. Preservation conditions during deposition and burial are modeled as a function of water depth when oxic water conditions are assumed. Two optional scenarios to represent oxygen deficiency in the water column can be chosen arbitrarily by the user: 1) an oxygen-minimum-zone scenario that is modeled as a function of surface-water productivity or 2) an anoxic-bottom-water scenario. Each scenario includes only a single pathway from input parameters to predicted source-rock potential. The model requires calibration with analytical data from well samples to provide a quantitative prediction of source-rock potential and type away from well control. OF-Mod uses the same set of processes and functions for all geological ages. OF-Mod publications include: Mann et al., “OF-Mod: an organic facies modelling tool,” Applications of numerical modelling in stratigraphy and basin analysis, Mountney and Burgess, Editors, London, UK, page 31 (2000); Knies and Mann, “Depositional environment and source rock potential of Miocene strata from the central Fram Strait: introduction of a new computing tool for simulating organic facies variations,” Marine and Petroleum Geology, 19(7), 811-828 (2002); and Mann and Zweigel, “Modelling source rock distribution and quality variations: The OF-Mod approach,” Analogue and Numerical Forward Modelling of Sedimentary Systems; from Understanding to Prediction, de Boer et al. ed's., Special Publication number 39 of the International Association of Sedimentologists (2007).
Merlin
“Merlin” claims to be a deterministic linear/serial workflow for forward source-rock prediction within a Geographic Information System (GIS) framework developed by Fugro-Robertson (Harris et al., 2006, “Palaeogeographic and Geological Constraints on Coupled Ocean-Atmosphere Palaeo-Earth Systems Modeling for Source Rock Prediction in Frontier Basins,” (2006) http://aapg.confex.com/aapg/2006int/techprogram/A106819.htm). A palaeo-environment map, gridded in GIS, provides the topographic and bathymetric boundary conditions for coupled ocean-atmosphere general circulation models and a barotropic model to simulate palaeotides. A series of “predictive masks” (also known as spatial filters) are combined in series (Boolean intersections) in a single pathway to derive a map of predicted source-rock potential in terms of total organic carbon content (TOC). The predicted source potential at each point is represented by a single deterministic value of TOC. The “predictive masks” are applied uniformly across all latitudes and are intended to account for the processes responsible for nutrient supply, organic productivity, and accumulation of organic-matter rich sediments together with dilutional processes responsible for the elimination of source rock potential. The current implementation of this process includes only six “masks”: 1) upwelling productivity, 2) storm productivity, 3) decay during settling, 4) tidal bed stress, 5) consumption by growth of benthic carbonates, and 6) organic-matter focusing (or “tidal sweep”). An area must pass all six “predictive masks” (i.e., satisfy all six spatial filters) to have significant source potential.
Thus, in general terms,Merlin Source-Rock Quality={Organic Matter Production}*{Fraction lost by Decay, Consumption, & Non-accumulation}*{Fraction concentrated or dispersed by gravity flow}or in concise algebraic form,Merlin Source-Rock Quality={X+Y}*A*B*C*D     where: X=amount of primary production of organic carbon due to Number of months of upwelling (in mgC/m2/year),            Y=amount of primary production of organic carbon due to Atmospheric Eddy Kinetic Energy (in mgC/m2/year),        A=fraction decrease due to Decay with settling through water column (≦1)        B=fraction decrease due to Non-accumulation through tidal bed shear stress (≦1),        C=fraction decrease due to Carbonate consumption (≦1)        D=fraction increase or decrease due to Gravity resedimentation.a form which is, by inspection and mathematical definition, a linear function. For all geological ages the “predictive masks” are the same and are combined in the same linear/serial deterministic manner with the same relative weighting factors.SourceRocker        
The Gandolph proposal by Geomark and Scotese (2005, p. 10) claims that                “SourceRocker is a heuristic computer program that incorporates predictive criteria relating geography, climate, and ocean state to hydrocarbon source bed deposition. [“Heuristic: providing aid or direction in the solution of a problem but otherwise unjustified or incapable of justification . . . ” Webster's Third New International Dictionary of the English Language (1986)] Using pattern-recognition and expert system-type rules, SourceRocker incorporates information about primary productivity, the likelihood of organic carbon preservation, and other important environmental effects, such as dilution due to [clastic] sediment influx, to estimate the type, quality, and quantity of potential source rocks on an basin/sub-basin scale.”        
Its goal is to derive a single set of empirical “rules” for forward source prediction from ocean and atmospheric conditions that apply to all geological ages using pattern-recognition and expert system-type rules. It postulates no physical, chemical, or biological processes or controls a priori. This approach uses a paleogeographic map for a particular geological time as input to an ocean-atmosphere model (FOAM: Fast Ocean-Atmosphere Model—developed as a joint effort between scientists in the Mathematics and Computer Science Division of Argonne National Laboratory and the Space Science and Engineering Center at the University of Wisconsin-Madison; http://www-unix.mcs.anl.gov/foam/index.html). In parallel, it classifies a series of oil and rock samples from that particular geological time into geochemical families. It then compares the outputs of the ocean-atmosphere model to only the geochemical families of the oils to establish empirical correlations that enable the prediction of source rocks away from sample control on that particular paleogeographic map. (Paleogeography is used almost exclusively as a boundary condition for the ocean-atmosphere forward modeling.) Thus it attempts to predict the type, quality, and quantity of potential source rocks from direct correlations of oil families to ocean-atmosphere conditions. These conditions are “hand-crafted” for each time interval to fit the paleo-reconstructions. (This description is derived from promotional materials written by GeoMark Ltd and Scotese in 2005: [www.geomarkresearch.com/res/Other%20Proposals/Gandolph%20Proposal%20(short)%2011.pdf]; it is unclear from the published literature what progress has been made on constructing a working program.)
In contrast to these linear, deterministic approaches, it has been shown recently that ORRs accumulate through a wide range of combinations of the competing processes of primary organic matter production, organic matter destruction, and organic matter dilution (Bohacs et al., “Production, Destruction, Dilution, and Accommodation—the many paths to source-rock development.,” in Harris, N. (editor) The deposition of organic carbon-rich sediments: Mechanisms, Models and Consequences, SEPM Special Publication 82, p. 61-101 (2005)). These authors report on case studies of three source-rock units wherein each unit is interpreted in terms of varying combinations of all the proximate factors of production, destruction, and dilution. The paper concentrates on demonstrating that hydrocarbon source rocks accumulate in a range of depositional settings. What is needed is a source rock predictive method that takes such nonlinear complexity into consideration. The present invention satisfies this need.